-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\knm4642\Dropbox\Nha Meo Heo Beo\_JMP\WORKING FOLDER\Table III_Effect on quality-weighted patents.log
  log type:  text
 opened on:  18 Feb 2026, 23:44:48

. 
. //PREPARE DATA
. use "Baseline CEO firm year sample.dta", clear

. * construct additional variables
. gen share_f1allpat_new_topq10 = f1allpat_new_topq10/f1allpat
(40,087 missing values generated)

. replace share_f1allpat_new_topq10 = 0 if share_f1allpat_new_topq10 == .
(40,087 real changes made)

. gen ash_f1avgcitff = asinh(f1allpat_citff/f1allpat)
(37,894 missing values generated)

. replace ash_f1avgcitff = 0 if ash_f1avgcitff == .
(37,894 real changes made)

. gen ash_f1avgxi = asinh(f1uspat_xi/f1uspat) if year < 2008
(46,310 missing values generated)

. replace ash_f1avgxi = 0 if f1uspat == 0 & year < 2008
(18,679 real changes made)

. * set globals
. global firm = "firmage firmage2"

. global ceo = "gender age age2 yrinco i.education"

. global sample = "year < 2012 & !nonUS"

. global cluster = "mainethcode"

. 
. 
. //PREPARE TABLE
. eststo clear

. eststo col1: /// explorative patents
>         reghdfe ash_f1allpat_new_topq10 trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      20.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8425
                                                  Adj R-squared   =     0.8204
                                                  Within R-sq.    =     0.0016
Number of clusters (mainethcode) =         38     Root MSE        =     0.5135

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1all~10 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0643588   .0133903     4.81   0.000     .0372275    .0914901
     firmage |  -.0071079   .0017813    -3.99   0.000    -.0107172   -.0034986
    firmage2 |   1.77e-06   .0000649     0.03   0.978    -.0001297    .0001332
      gender |  -.0205627   .0203599    -1.01   0.319    -.0618159    .0206904
         age |  -.0011993   .0090112    -0.13   0.895    -.0194577    .0170592
        age2 |  -5.14e-06   .0000749    -0.07   0.946    -.0001569    .0001467
      yrinco |   .0033491   .0009669     3.46   0.001     .0013899    .0053082
             |
   education |
          2  |   .0340436   .0315309     1.08   0.287    -.0298439    .0979312
          3  |   .0521885   .0216655     2.41   0.021     .0082901    .0960869
          4  |   .0623362   .0307183     2.03   0.050     .0000951    .1245774
             |
       _cons |   .4767572   .2346809     2.03   0.049     .0012484    .9522659
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col1, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col2: /// disruptive patents
>         reghdfe ash_f1allpat_posCD trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      27.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8807
                                                  Adj R-squared   =     0.8640
                                                  Within R-sq.    =     0.0013
Number of clusters (mainethcode) =         38     Root MSE        =     0.5112

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allp~D | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0438212   .0147913     2.96   0.005     .0138513    .0737912
     firmage |  -.0070496    .002244    -3.14   0.003    -.0115964   -.0025029
    firmage2 |  -1.81e-06   .0000436    -0.04   0.967    -.0000901    .0000865
      gender |   -.032912   .0227839    -1.44   0.157    -.0790765    .0132525
         age |  -.0011291   .0096327    -0.12   0.907    -.0206467    .0183886
        age2 |  -5.84e-06   .0000781    -0.07   0.941    -.0001641    .0001524
      yrinco |   .0032984   .0007205     4.58   0.000     .0018384    .0047583
             |
   education |
          2  |    .013536   .0561143     0.24   0.811    -.1001624    .1272345
          3  |   .0300383   .0409969     0.73   0.468    -.0530294    .1131059
          4  |   .0462011   .0521041     0.89   0.381    -.0593719    .1517741
             |
       _cons |   .7039064   .2542824     2.77   0.009     .1886814    1.219131
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col2, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col3: /// top-decile-importance patents
>         reghdfe ash_f1uspat_sig_topq10 trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin     
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      24.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8463
                                                  Adj R-squared   =     0.8248
                                                  Within R-sq.    =     0.0026
Number of clusters (mainethcode) =         38     Root MSE        =     0.6329

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1usp~10 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0988694   .0257634     3.84   0.000     .0466677     .151071
     firmage |  -.0149082   .0043077    -3.46   0.001    -.0236363     -.00618
    firmage2 |  -.0001599   .0000753    -2.12   0.041    -.0003126   -7.29e-06
      gender |  -.0012837   .0425621    -0.03   0.976    -.0875228    .0849553
         age |  -.0163972   .0110919    -1.48   0.148    -.0388715    .0060772
        age2 |   .0001492   .0000989     1.51   0.140    -.0000511    .0003495
      yrinco |   .0021836   .0010243     2.13   0.040     .0001082     .004259
             |
   education |
          2  |  -.0390047   .1108071    -0.35   0.727    -.2635213    .1855119
          3  |  -.0273211   .0876308    -0.31   0.757    -.2048779    .1502357
          4  |   .0136111   .1073516     0.13   0.900     -.203904    .2311262
             |
       _cons |   1.093176   .3059772     3.57   0.001     .4732072    1.713145
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col3, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col4: /// backward NPL citation-weighted
>         reghdfe ash_f1allpat_npl trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      12.45
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8381
                                                  Adj R-squared   =     0.8154
                                                  Within R-sq.    =     0.0035
Number of clusters (mainethcode) =         38     Root MSE        =     1.0092

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allp~l | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .1017759   .0297178     3.42   0.002     .0415619    .1619899
     firmage |  -.0410706   .0163302    -2.52   0.016    -.0741587   -.0079826
    firmage2 |   .0005062   .0000656     7.72   0.000     .0003733    .0006391
      gender |   .0618238   .0353908     1.75   0.089    -.0098847    .1335324
         age |  -.0231197   .0129397    -1.79   0.082    -.0493381    .0030987
        age2 |   .0001981   .0001049     1.89   0.067    -.0000144    .0004107
      yrinco |   .0038385   .0008691     4.42   0.000     .0020776    .0055993
             |
   education |
          2  |  -.0526251   .1296409    -0.41   0.687    -.3153025    .2100523
          3  |  -.0272948    .124152    -0.22   0.827    -.2788506     .224261
          4  |  -.0057072   .1193461    -0.05   0.962    -.2475253    .2361109
             |
       _cons |   1.835127   .4247537     4.32   0.000     .9744945     2.69576
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col4, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col5: /// technological scope-weighted
>         reghdfe ash_f1allpat_sco trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      41.40
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8855
                                                  Adj R-squared   =     0.8694
                                                  Within R-sq.    =     0.0021
Number of clusters (mainethcode) =         38     Root MSE        =     0.6931

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allp~o | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0596401   .0230731     2.58   0.014     .0128895    .1063907
     firmage |  -.0178265   .0030349    -5.87   0.000    -.0239758   -.0116773
    firmage2 |   .0002145   .0000595     3.61   0.001      .000094    .0003351
      gender |   -.000652   .0423718    -0.02   0.988    -.0865055    .0852014
         age |  -.0034724   .0134118    -0.26   0.797    -.0306473    .0237025
        age2 |   .0000114   .0001108     0.10   0.919    -.0002131    .0002359
      yrinco |   .0042479   .0005329     7.97   0.000     .0031681    .0053277
             |
   education |
          2  |    .040048   .0525141     0.76   0.451    -.0663557    .1464516
          3  |   .0578933   .0360644     1.61   0.117    -.0151802    .1309668
          4  |   .0947012   .0485126     1.95   0.059    -.0035947    .1929972
             |
       _cons |   1.202622    .362264     3.32   0.002     .4686059    1.936639
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col5, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col6: /// explorative patent share       
>         reghdfe share_f1allpat_new_topq10 trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =       4.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0008
                                                  R-squared       =     0.4250
                                                  Adj R-squared   =     0.3443
                                                  Within R-sq.    =     0.0003
Number of clusters (mainethcode) =         38     Root MSE        =     0.2566

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
share_f1a~10 | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0112031   .0044086     2.54   0.015     .0022704    .0201358
     firmage |  -.0056393   .0042483    -1.33   0.192    -.0142472    .0029686
    firmage2 |   7.21e-06   .0000152     0.47   0.639    -.0000237    .0000381
      gender |   .0033759   .0124602     0.27   0.788    -.0218708    .0286227
         age |    .000504   .0045408     0.11   0.912    -.0086965    .0097044
        age2 |  -7.87e-06   .0000411    -0.19   0.849    -.0000911    .0000753
      yrinco |  -.0000852   .0005051    -0.17   0.867    -.0011087    .0009383
             |
   education |
          2  |    .014364   .0145524     0.99   0.330    -.0151219      .04385
          3  |   .0171021   .0135453     1.26   0.215    -.0103433    .0445474
          4  |   .0231345   .0165373     1.40   0.170    -.0103733    .0566423
             |
       _cons |   .1983248   .1498127     1.32   0.194    -.1052245    .5018741
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col6, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col7: /// average forward citations      
>         reghdfe ash_f1avgcitff trust_sd ${firm} ${ceo} if ${sample}, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      25.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6825
                                                  Adj R-squared   =     0.6379
                                                  Within R-sq.    =     0.0008
Number of clusters (mainethcode) =         38     Root MSE        =     0.8760

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1avgc~f | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0429807   .0190052     2.26   0.030     .0044726    .0814888
     firmage |  -.0295756   .0075871    -3.90   0.000    -.0449486   -.0142025
    firmage2 |   .0000759   .0000621     1.22   0.229    -.0000499    .0002017
      gender |   .0774087   .0518517     1.49   0.144     -.027653    .1824703
         age |  -.0172028   .0149692    -1.15   0.258    -.0475333    .0131278
        age2 |    .000164   .0001299     1.26   0.215    -.0000992    .0004272
      yrinco |   .0017206   .0012249     1.40   0.168    -.0007612    .0042025
             |
   education |
          2  |  -.0227476    .122361    -0.19   0.854    -.2706745    .2251792
          3  |  -.0150186    .111462    -0.13   0.894    -.2408621    .2108248
          4  |   .0082228   .1174747     0.07   0.945    -.2298036    .2462492
             |
       _cons |   1.667138    .397245     4.20   0.000     .8622437    2.472033
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col7, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col8: /// average patent value   
>         reghdfe ash_f1avgxi trust_sd ${firm} ${ceo} if ${sample} & year < 2008, ///
>         a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =     20,218
Absorbing 2 HDFE groups                           F(  10,     37) =      14.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7162
                                                  Adj R-squared   =     0.6632
                                                  Within R-sq.    =     0.0038
Number of clusters (mainethcode) =         38     Root MSE        =     0.6443

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
 ash_f1avgxi | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0582396   .0243413     2.39   0.022     .0089195    .1075598
     firmage |  -.0057161   .0043871    -1.30   0.201    -.0146052    .0031729
    firmage2 |  -.0004484   .0001164    -3.85   0.000    -.0006842   -.0002125
      gender |   .0014251   .0430307     0.03   0.974    -.0857634    .0886136
         age |  -.0149502   .0086528    -1.73   0.092    -.0324825     .002582
        age2 |   .0001635   .0000778     2.10   0.042     5.93e-06     .000321
      yrinco |   -.000097   .0007927    -0.12   0.903    -.0017031    .0015092
             |
   education |
          2  |  -.0305143   .0464673    -0.66   0.515     -.124666    .0636373
          3  |   .0069757   .0386743     0.18   0.858    -.0713859    .0853373
          4  |   .0575769   .0580829     0.99   0.328    -.0601102    .1752641
             |
       _cons |   .8673662   .2646586     3.28   0.002      .331117    1.403615
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3168           0        3168     |
        year |         8           1           7     |
-----------------------------------------------------+

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      20218       3168

.                 eststo col8, add(nofirms r(ndistinct))
(e(nofirms) = 3168 added)

. 
. lab var ash_f1allpat_new_topq10     "Explorative pat"

. lab var ash_f1allpat_posCD          "Disruptive pat"

. lab var ash_f1uspat_sig_topq10      "Patent importance"

. lab var ash_f1allpat_npl            "Backward NPL cites"

. lab var ash_f1allpat_sco            "Tech scope"

. lab var share_f1allpat_new_topq10   "(Explor pat)"

. lab var ash_f1avgcitff              "(Avg cites)"

. lab var ash_f1avgxi                 "(Avg value)"

. esttab /*using "Table III_Effect on quality-weighted patents.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         collabels(none) label varwidth(18) modelwidth(15) ///
>         mgroups("arsinh(Future quality-weighted patents)" "Share" "arsinh" "arsinh", ///
>                 pattern(1 0 0 0 0 1 1 1) prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(trust_sd) coeflab(trust_sd "CEO's trust") ///
>         stats(FE controls N nofirms, fmt(%9.0fc %9.0fc) ///
>                 lab("Firm \& Year FEs" "Baseline controls" "Observations" "Firms"))

--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                   \multicolumn{5}{c}{arsinh(Future quality-weighted patents)}                                    \multicolumn{1}{c}{Share} \multicolumn{1}{c}{arsinh} \multicolumn
> {1}{c}{arsinh}
                               (1)                (2)                (3)                (4)                (5)                (6)                (7)                (8)   
                   Explorative pat     Disruptive pat    Patent import~e    Backward NPL ~s         Tech scope       (Explor pat)        (Avg cites)        (Avg value)   
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
CEO's trust                  0.064***           0.044***           0.099***           0.102***           0.060**            0.011**            0.043**            0.058** 
                           (0.013)            (0.015)            (0.026)            (0.030)            (0.023)            (0.004)            (0.019)            (0.024)   
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Firm \& Year FEs                 X                  X                  X                  X                  X                  X                  X                  X   
Baseline controls                X                  X                  X                  X                  X                  X                  X                  X   
Observations                29,384             29,384             29,384             29,384             29,384             29,384             29,384             20,218   
Firms                        3,598              3,598              3,598              3,598              3,598              3,598              3,598              3,168   
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. cap log close
